Data-sharing is an immense enabler of scientific advancements. When researchers choose to make their data publicly available, they are allowing their work to contribute far beyond the original findings. Making research data more accessible also fosters transparency and trust in their work, enables other researchers to reproduce and validate their findings, and ultimately, contributes to the pace of scientific discovery by allowing others to reuse and build on top of the data. Fortunately, cloud technology has made it easier than ever to share data across major research institutions. Empowered by tools that include Microsoft Azure, researchers are relying more and more on digital collaboration and open source software to drive scientific breakthroughs.

Watch this video to learn how researchers at Australian National University (ANU) are using Azure to build on each other’s findings and avoid a siloed approach to data that leads to slower research pipelines.

At Microsoft’s annual Build developer conference, there were several updates announced for Microsoft Teams. According to veteran participant and Forbes contributor Patrick Moorhead, the integration of Teams with Microsoft Power Platform “was the biggest story out of the conference this year, as it turns Teams into essentially a full-blown platform. With the lack of developers globally, I think this combination could enable some very powerful capabilities.”

Power BI is also getting further integrated into Teams, notes Moorhead. Users will be able to import and share reports, or merely charts from reports, from the new ‘Share to Teams’ button in the Power BI portal. “Additionally, when a chart is shared to a Teams conversation it will now include a rich thumbnail preview, and an adaptive card that Microsoft says will enable users to take action on said chart,” writes Moorhead.

There’s lots more to take note of for the improvements around Microsoft Teams and its far-reaching capabilities. Read Moorhead’s entire article, “Spotlight on ‘Teams as a Platform’ at Virtual Microsoft Build 2020” for an overview of these developments.

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Dynamics 365 for Sales Professional was built to tackle the biggest challenges faced by sales professionals, especially unclear expectations and sales tools and data overload. Cut through the clutter and ambiguity with Dynamics 365 for Sales Professional.

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From autonomous vehicles, predictive analytics applications, and facial recognition, to chatbots, virtual assistants, cognitive automation, and fraud detection, the use cases for AI span dozens of industries. Regardless of the AI application, though, these use cases all have a common aspect. After implementing thousands of AI projects, experts have come to realize that despite all of the diversity in applications, AI use cases fall into one or more of seven common patterns. One of them—the pattern-matching pattern—has allowed machines to digest large amounts of data to identify patterns, anomalies, and outliers in the data, so organizations can unearth previously undiscovered insights in their datasets.

In this article, you’ll learn how pattern-matching is being put to use in today’s organizations to prevent fraud, find the best job candidates, manage inventories in times of crisis, and empower data scientists with new perspectives on how to improve critical processes.

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